End-to-end machine learning regression model for predicting housing prices in Bengaluru, with Heroku deployment.
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Updated
Jan 1, 2022 - Jupyter Notebook
End-to-end machine learning regression model for predicting housing prices in Bengaluru, with Heroku deployment.
Metis project 2/7
School exercise - Multivariate Statistical Methods subject
This model trains according to the data and makes a Polynomial Regression curve of degree 16. The model is regularized using Ridge regression. It also compares the predicted values with original outputs and for different alphas.
In this series of notebooks, we will dive into each step of the data analysis process of a data set with some information about a list of cars and several attibutes, including their prices. So essentially we will develop a model to predict cars price.
Approach to some basic Machine Learning Techniques.
Predictive Analytics for Real Estate Investment: A Regression Model Approach for Surprise Housing in the Australian Market using Regularization methods (Ridge and Lasso)
A small project addressing a regression problem explains implementation of multiple linear regression techniques, hyperparameter tuning, collinearity, model overfitting and complexity using LASSO, Ridge and Elastic net
Regression models(lasso, ridge, DT) using NumPy.
Exploring World Development Indicators: Identifying relationship between Health Indicators using Linear Regression & Classification of Income Group based on Health Indicators using Logistic Regression.
Building Advanced regression models (Lasso and Ridge) for house price prediction in the Australian market
As part of the UCSanDiego online course "Machine Learning Fundamentals"
Model Building and Testing using Ridge, Lasso and ElasticNet Methods
A series of Statistical Modelling assignments with the use of R. Applications of Linear, Polynomial, Logistic and Poisson Regression in various datasets
Advanced Regression model on Housing Data from Australia for my Upgrad - IIITB AI ML PG Course
It was a competition on KAGGLE for prediction on the most sales products on bikes via their features
In this project, I build 20+ models predicting Spotify song popularity. These include neural networks, Lasso and Ridge regression models. I also leverage OpenAI chat-completion API to engineer features from song lyrics.
Gemstone Price Prediction - End to End ML Project with AWS deployment
Practical Implementation of Linear Regression on Boston Housing Price Prediction
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